The semiconductor industry currently uses different types of semiconductor-based imagers, such as charge coupled devices (CCDs), complementary metal oxide semiconductor (CMOS) devices, photodiode arrays, charge injection devices and hybrid focal plane arrays, among others.
Solid-state image sensors, also known as imagers, were developed in the late 1960s and early 1970s primarily for television image acquisition, transmission, and display. An imager absorbs incident radiation of a particular wavelength (such as optical photons, x-rays, or the like) and generates an electrical signal corresponding to the absorbed radiation. There are a number of different types of semiconductor-based imagers, including CCDs, photodiode arrays, charge injection devices (CIDs), hybrid focal plane arrays, and CMOS imagers. Current applications of solid-state imagers include cameras, scanners, machine vision systems, vehicle navigation systems, video telephones, computer input devices, surveillance systems, auto focus systems, star trackers, motion detector systems, image stabilization systems and other image based systems.
These imagers typically consist of an array of pixel cells containing photosensors, where each pixel cell produces a signal corresponding to the intensity of light impinging on that element when an image is focused on the array. These signals may then be used, for example, to display a corresponding image on a monitor or otherwise used to provide information about the optical image. The photosensors are typically photogates, phototransistors, photoconductors or photodiodes, where the conductivity of the photosensor or the charge stored in a diffusion region corresponds to the intensity of light impinging on the photosensor. The magnitude of the signal produced by each pixel cell, therefore, is proportional to the amount of light impinging on the photosensor.
CMOS active pixel sensor (APS) imaging devices are known in the art. These imaging devices include an array of pixel cells, arranged in rows and columns, that convert light energy into electric signals. Each pixel cell includes a photodetector and one or more active transistors. The transistors typically provide amplification, read-out control and reset control, in addition to producing the electric signal output from the cell.
While CCD technology has a widespread use, CMOS imagers are being increasingly used as low cost imaging devices. A fully compatible CMOS sensor technology enabling a higher level of integration of an image array with associated processing circuits is beneficial to many digital imager applications.
A CMOS imager circuit includes a focal plane array of pixel cells, each one of the cells including a photoconversion device, for example, a photogate, photoconductor, phototransistor, or a photodiode for accumulating photo-generated charge in a portion of the substrate. A readout circuit is connected to each pixel cell and includes at least an output transistor, which receives photogenerated charges from a doped diffusion region and produces an output signal that is periodically read out through a pixel access transistor. The imager may optionally include a transistor for transferring charge from the photoconversion device to the diffusion region or the diffusion region may be directly connected to or part of the photoconversion device. A transistor is also typically provided for resetting the diffusion region to a predetermined charge level before it receives the photoconverted charges.
In a CMOS imager, the active elements of a pixel cell perform the necessary functions of: (1) photon to charge conversion; (2) accumulation of image charge; (3) transfer of charge to a floating diffusion region accompanied by charge amplification; (4) resetting the floating diffusion region to a known state; (5) selection of a pixel for readout; and (6) output and amplification of a signal representing pixel cell charge. Photo-charge may be amplified when it moves from the initial charge accumulation region to the floating diffusion region. The charge at the floating diffusion region is typically converted to an output voltage by a source follower output transistor.
A digital-output CMOS imager has a number of analog-to-digital converters (ADC) which digitize the data pixels put out through above functions (1)-(6). Generally, such CMOS imagers have digital data-path following ADC for noise reduction, black level compensation, various formatted output and so on. The data-path for image processing of a conventional image sensor device is shown in FIG. 1. In the conventional image sensor device, each functional block in the image processing data-path communicates over a bus with a fixed-bit bus width. The data is processed from left to right, keeping an N-bit data width, with “N” being defined by the resolution of the analog-to-digital converter (ADC) used in the image sensor device. For example, an image sensor using a 12-bit ADC has a 12-bit bus width (i.e., N=12).
As can be seen from FIG. 1, after analog-to-digital conversion, digital data is received over an N-bit wide data path 11 and the image is dithered at processing block 10. Dithering, also called halftoning or color reduction, is a well known process of rendering an image on a display device with fewer colors than are in the images. The number of different colors in an image or on a device used to display the image is called color resolution. Dithering scatters different colored pixels in an image to make it appear as though there are intermediate colors in images with a limited color palette.
The data is then forwarded to a defect correction processing block 12 over an N-bit wide data path 13 where any defects in the image data are corrected. Defect correction is the process of substituting pixel defects (i.e., single dark or bright pixels) with neighboring pixel data to correct any defects in the pixel data.
The data is sent over another N-bit wide path 15. Any column fixed pattern noise in the data is compared to column fixed pattern calibration values 14, which have been stored in an offset RAM 16, at the column fixed pattern noise correction processing block 18. The data is then sent to the row fixed pattern noise correction processing block 20 over an N-bit wide data path 17. The data is then sent to the digital gain processing block 22 over another N-bit wide path 19.
After digital gain is applied to the data, the data is next sent to a column binning processing block 24 over an N-bit wide data path 21. Binning is the accumulation or interpolation of the charge of multiple pixels and reading them out in a single operation. By incorporating binning into the readout circuitry, various sub-resolution processes can be implemented to minimize aliasing effects. The binning operation can be done using any suitable techniques, including but not limited to the operations described in Zhou, Z., Frame-Transfer CMOS Active Pixel Sensor with Pixel Binning, IEEE Electronic Devices, October 1997, pp. 1764-68, incorporated herein by reference. Finally, the data is output over an N-bit wide data path 23.
Due in part to the fixed bus width throughout the image processing data-path, the image sensor device using above structure will incur computation errors in the image processing. Because of the fixed bit bus width, the data needs to be truncated and the fractional part of the data that is generated from the image sensor device after calculation at each processing block is lost. The loss of the fractional part of the data is magnified when the data is amplified. The accumulated errors are magnified at the digital gain when the data is “G”-time amplified during the “Digital Gain” procedure in the image processing. Typically the digital gain, G, can be 8 or 16. The image quality of the image sensor device is noticeable at even the second or third least significant bits (LSB) of the digital data.
FIG. 2 illustrates the error produced by the data-path for image processing with 16-time amplifying, G according to FIG. 1. As can be seen from the figure, the error in the data path according to FIG. 1 is the difference between the output from digital gain (horizontal lines) and the ideal linear curve. FIG. 2 shows the difference between “G*x” and “integer part of G*x” where x is input data to Digital Gain. The scale of the y-axis is for 16-time amplifying.
There is a need, therefore, for imaging devices which have improved image quality. A method of reducing computational errors in the image processing data paths of an image sensor device is also needed.